We also utilize VGG-Sound [1]}, which similarly provides over 200k human-labeled video clips (in 10-second segments) and the 310 corresponding audio classes. We finally use 182,342 videos for training due to missing clips. Note that a pair of images from the middle frame of each video clip and its corresponding class label is used as an image-text input pair for training our model.
